Big Data for Sustainable Transport Planning

Slides presented at a 'Big Data and Transport' symposium organised by the Institute for Transport Studies (ITS) and the Consumer Data Research Centre (CDRC) in Leeds, UK.

Transcript

1. Big Data for sustainable transport planning Robin Lovelace Researcher, CDRC @robinlovelace
2. Structure 1. What even is ‘Big Data’ 2. Data on cycling safety 3. Understanding travel patterns 4. Prioritising new investment
3. What is Big Data?
4. Various definitions • 1 Billion+ rows? • 3 or 4 V’s? • Software needs? • Hardware needs? • Complexity?
5. Part I: Data to improve safety
6. New insights on populations at risk
7. Estimates of cycling riskiness
8. Part II: Better understanding of travel patterns “Non work flows” are hard to estimate New sources of data can help • Mobile phone data ( access and accuracy) • Dedicated tracking apps • Passive data collection (Google Maps)
9. E.g. Cycle Hackney
10. Current research: Twitter to calibrate SIM
11. Scenarios of cycling: national
12. Part III: Prioritising new investment in walking and cycling
13. Where do people travel? https://github.com/npct/pct
14. Input: work-time population
15. Making data come alive! https://robinlovelace.shinyapps.io/fixMyPath/
16. The future of big data in transport • Smart tracking and behaviour of driverless cars • Real-time bus route decision making • Intelligent congestion charging zones • A ‘post-carbon’ transport system
17. Thanks for listening! r.lovelace@leeds.ac.uk @robinlovelace slides: robinlovelace.net
18. Research interests